bloomz.cpp
llama.cpp
| bloomz.cpp | llama.cpp | |
|---|---|---|
| 4 | 782 | |
| 806 | 58,425 | |
| - | - | |
| 6.0 | 10.0 | |
| about 1 year ago | 3 days ago | |
| C | C++ | |
| MIT License | MIT License |
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bloomz.cpp
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My largest ever quants, GPT 3 sized! BLOOMZ 176B and BLOOMChat 1.0 176B
Possibly. There's a llama.cpp fork called bloomz.cpp but it's not been updated in 2 months. So it's not going to support any of the fancy new quantisation methods, performance improvements, GPU acceleration, etc.
- Bloomz.cpp: C++ implementation for BLOOM models
- Bloomz.cpp: Run multilingual BLOOM model with C++
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[N] bloomz.cpp: Run any BLOOM-like model in pure C++
bloomz.cpp allows running inference of BLOOM-like models in pure C/C++ (inspired by llama.cpp). It supports all models that can be loaded with BloomForCausalLM.from_pretrained(). For example, you can achieve 16 tokens per second on a M1 Pro.
llama.cpp
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IBM Granite: A Family of Open Foundation Models for Code Intelligence
if you can compile stuff, then looking at llama.cpp (what ollama uses) is also interesting: https://github.com/ggerganov/llama.cpp
the server is here: https://github.com/ggerganov/llama.cpp/tree/master/examples/...
And you can search for any GGUF on huggingface
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Ask HN: Affordable hardware for running local large language models?
Yes, Metal seems to allow a maximum of 1/2 of the RAM for one process, and 3/4 of the RAM allocated to the GPU overall. There’s a kernel hack to fix it, but that comes with the usual system integrity caveats. https://github.com/ggerganov/llama.cpp/discussions/2182
- Xmake: A modern C/C++ build tool
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Better and Faster Large Language Models via Multi-Token Prediction
For anyone interested in exploring this, llama.cpp has an example implementation here:
https://github.com/ggerganov/llama.cpp/tree/master/examples/...
- Llama.cpp Bfloat16 Support
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Fine-tune your first large language model (LLM) with LoRA, llama.cpp, and KitOps in 5 easy steps
Getting started with LLMs can be intimidating. In this tutorial we will show you how to fine-tune a large language model using LoRA, facilitated by tools like llama.cpp and KitOps.
- GGML Flash Attention support merged into llama.cpp
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Phi-3 Weights Released
well https://github.com/ggerganov/llama.cpp/issues/6849
- Lossless Acceleration of LLM via Adaptive N-Gram Parallel Decoding
- Llama.cpp Working on Support for Llama3
What are some alternatives?
libvips - A fast image processing library with low memory needs.
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
lm-evaluation-harness - A framework for few-shot evaluation of language models.
gpt4all - gpt4all: run open-source LLMs anywhere
vosk - VOSK Speech Recognition Toolkit
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
ggml - Tensor library for machine learning
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
ggml - Tensor library for machine learning
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM
FastChat - An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
rust-gpu - 🐉 Making Rust a first-class language and ecosystem for GPU shaders 🚧